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Interactive video retrieval in the age of deep learning
ConferencePaper (Artikel, die in Tagungsbänden erschienen sind)
 
ID 4523927
Author(s) Lokoč, Jakub; Schöffmann, Klaus; Bailer, Werner; Rossetto, Luca; Gurrin, Cathal
Author(s) at UniBasel Rossetto, Luca
Year 2019
Year: comment 2019
Title Interactive video retrieval in the age of deep learning
Book title (Conference Proceedings) Proceedings of the 2019 on International Conference on Multimedia Retrieval
Place of Conference Ottawa, Canada
Publisher ACM
Pages 2-4
ISSN/ISBN 978-1-4503-6765-3
Abstract We present a tutorial focusing on video retrieval tasks, where state-of-the-art deep learning approaches still benefit from interactive decisions of users. The tutorial covers general introduction to the interactive video retrieval research area, state-of-the-art video retrieval systems, evaluation campaigns and recently observed results. Moreover, a significant part of the tutorial is dedicated to a practical exercise with three selected state-of-the-art systems in the form of an interactive video retrieval competition. Participants of this tutorial will gain a practical experience and also a general insight of the interactive video retrieval topic, which is a good start to focus their research on unsolved challenges in this area.
URL https://doi.org/10.1145/3323873.3326588
edoc-URL https://edoc.unibas.ch/73833/
Full Text on edoc No
Digital Object Identifier DOI 10.1145/3323873.3326588
ISI-Number WOS:000482188900002
 
   

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